منابع مشابه
Nelson–Aalen Estimator
The Nelson–Aalen estimator is a nonparametric estimator which may be used to estimate the cumulative hazard rate function from censored survival data (see Survival Distributions and Their Characteristics). Since no distributional assumptions are needed, one important use of the estimator is to check graphically the fit of parametric models, and this is the reason why it was originally introduce...
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Parametric identification of linear time-invariant (LTI) systems with output-error (OE) type of noise model structures has a well-established theoretical framework. Different algorithms, like instrumental-variables approaches or prediction error methods (PEMs), have been proposed in the literature to compute a consistent parameter estimate for linear OE systems. Although the prediction error me...
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BACKGROUND Intraclass correlation coefficients (ICCs) are used in a wide range of applications. However, most commonly used estimators for the ICC are known to be subject to bias. METHODS Using second order Taylor series expansion, we propose a new bias-corrected estimator for one type of intraclass correlation coefficient, for the ICC that arises in the context of the balanced one-way random...
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The Beveridge–Nelson decomposition calculates trend and cycle for an integrated time series. However, there are two ways to interpret the results from the decomposition. One interpretation is that the optimal long-run forecast (minus any deterministic drift) used to calculate the Beveridge–Nelson trend corresponds to an estimate of an unobserved permanent component. The other interpretation is ...
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Zhang in 2012 introduced a nonparametric estimator of Shannon’s entropy, whose bias decays exponentially fast when the alphabet is finite. We propose a methodology to estimate the bias of this estimator. We then use it to construct a new estimator of entropy. Simulation results suggest that this bias adjusted estimator has a significantly lower bias than many other commonly used estimators. We ...
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ژورنال
عنوان ژورنال: IOP Conference Series: Materials Science and Engineering
سال: 2021
ISSN: 1757-8981,1757-899X
DOI: 10.1088/1757-899x/1043/2/022013